269 citations · 562 across the 7 of their papers we have counts for
7 papers
Machine learning analysis of Photometric data from the Dark Energy Survey
Elcio Abdalla, Filipe B. Abdalla, Alessandro Marins +3
In order to retrieve cosmological parameters from photometric surveys, we need to estimate the distribution of the photometric redshift in the sky with excellent accuracy. We use a…
Dark Energy Survey Year 1 Results: A Precise H0 Measurement from DES Y1, BAO, and D/H Data
DES Collaboration, T. M. C. Abbott, F. B. Abdalla +88
We combine Dark Energy Survey Year 1 clustering and weak lensing data with Baryon Acoustic Oscillations (BAO) and Big Bang Nucleosynthesis (BBN) experiments to constrain the Hubble…
DES Science Portal: Computing Photometric Redshifts
Julia Gschwend, Aurelio Carnero Rosell, Ricardo Ogando +68
A significant challenge facing photometric surveys for cosmological purposes is the need to produce reliable redshift estimates. The estimation of photometric redshifts (photo-zs)…
Photometric redshifts and clustering of emission line galaxies selected jointly by DES and eBOSS
S. Jouvel, T. Delubac, J. Comparat +65
We present the results of the first test plates of the extended Baryon Oscillation Spectroscopic Survey. This paper focuses on the emission line galaxies (ELG) population targetted…
ANNz2 - photometric redshift and probability distribution function estimation using machine learning
Iftach Sadeh, Filipe B. Abdalla, Ofer Lahav
We present ANNz2, a new implementation of the public software for photometric redshift (photo-z) estimation of Collister and Lahav (2004), which now includes generation of full pro…
Cosmology with the SKA -- overview
Roy Maartens, Filipe B. Abdalla, Matt Jarvis +1
The new frontier of cosmology will be led by three-dimensional surveys of the large-scale structure of the Universe. Based on its all-sky surveys and redshift depth, the SKA is des…
Photometric redshift estimation using Gaussian processes
D. G. Bonfield, Y. Sun, N. Davey +4
We present a comparison between Gaussian processes (GPs) and artificial neural networks (ANNs) as methods for determining photometric redshifts for galaxies, given training set dat…